Insider Brief<\/p>\n
ABB Robotics is integrating Nvidia Omniverse libraries into its RobotStudio software to enable manufacturers to simulate and train AI-driven robots in highly accurate digital twin environments.<\/p>\n
The collaboration aims to close the long-standing \u201csim-to-real\u201d gap by allowing developers to generate synthetic data and train robots virtually with up to 99% accuracy before deployment in real-world production lines.<\/p>\n
Early deployments include Foxconn testing the system for consumer electronics assembly, with the technology expected to roll out to ABB\u2019s more than 60,000 RobotStudio users in the second half of 2026.<\/p>\n
PRESS RELEASE \u2014 ABB Robotics<\/a> announced today it is integrating Nvidia Omniverse libraries<\/a> into ABB Robotics\u2019 RobotStudio\u00ae to help manufacturers deploy physical AI<\/a> in real world robotics<\/a> applications.<\/p>\n \u201cToday, using Nvidia<\/a> accelerated computing and simulation technologies, we have removed the last barriers to making industrial and physical AI a reality at a global scale by closing the sim-to-real gap,\u201d said Marc Segura, President of ABB Robotics. \u201cFor more than 50 years, ABB Robotics has led the evolution of intelligent industrial automation, from pioneering the first generation of fully electric industrial robots to advancing digital twin simulation through RobotStudio\u00ae\u00a0and shaping a new area of autonomous and versatile mobile robots. Today\u2019s announcement with Nvidia brings physical AI to industry at scale.\u201d<\/p>\n The collaboration focuses on combining ABB Robotics\u2019 software programming, design and simulation suite, RobotStudio, with the physically accurate simulation power of Nvidia Omniverse libraries to close technology\u2019s long-standing \u2018sim-to-real\u2019 gap. Developers can simulate robots in digital twins and generate synthetic data to train their physical AI models, enabling businesses of all types and sizes to deploy AI-driven robotics for various industrial workflows.<\/p>\n Called RobotStudio HyperReality, the resulting physically accurate simulations and foundation models are endlessly optimized with real-world data feedback continuously improving the system. These models can be used to train any number of ABB robots, anywhere in the world, with the reliability and accuracy demanded by industry.<\/p>\n \u201cThe industrial sector needs physically accurate simulation to bridge the gap between virtual training and the real-world deployment of AI-driven robotics at scale,\u201d said Deepu Talla, vice president of robotics and edge AI at Nvidia. \u201cIntegrating Nvidia Omniverse libraries into RobotStudio brings advanced simulation and accelerated computing to ABB Robotics\u2019 unique virtual controller technology, accelerating how manufacturers of all sizes bring complex products to market.\u201d<\/p>\n Closing the \u2018sim-to-real\u2019 gap<\/p>\n The long-standing deficit between simulation accuracy and real-world lighting, materials and environments is known as the \u2018sim-to-real\u2019 gap. For decades, this gap has limited the ability of manufacturers to design and develop advanced manufacturing processes in the virtual world.<\/p>\n By integrating Nvidia Omniverse libraries into RobotStudio, ABB Robotics will deliver unprecedented robotics simulation and synthetic data generation capabilities that will allow intelligent robots to bridge this gap with up to 99 percent accuracy. ABB is the only robot manufacturer with a virtual controller running the same firmware as the hardware, ensuring near\u2011perfect correlation between simulation and real\u2011world performance. Combined with ABB Robotics\u2019 Absolute Accuracy technology, which reduces positioning errors from 8\u201315 mm to around 0.5 mm, ABB delivers unmatched precision in both virtual and physical environments, making it suited to high-precision industrial-grade applications.<\/p>\n This innovation enables manufacturers to design, test, and optimize production lines virtually, cutting setup and commissioning times by up to 80 percent, reducing costs by up to 40 percent by eliminating the need for physical prototypes, and accelerating time-to-market for complex products such as consumer electronics by 50 percent1.<\/p>\n ABB Robotics is also assessing the potential to integrate the Nvidia Jetson edge computing platform into its Omnicore controller to achieve real-time AI inference at the edge for its extensive robot portfolio. Today\u2019s announcement builds upon ABB Robotics\u2019 long-standing work with Nvidia, including the previous integration of Nvidia Jetson into ABB Robotics\u2019 VSLAM autonomous mobile robots as well as the development of gigawatt-scale AI data centers.<\/p>\n Real-world applications, today<\/p>\n RobotStudio HyperReality will serve industrial clients at any scale, across a breadth of industries and applications, with select customers already testing its capabilities ahead of a full release to ABB Robotics\u2019 60,000 RobotStudio customers worldwide in the second half of 2026.<\/p>\n Foxconn, the world\u2019s largest electronics contract manufacturer, is piloting the first joint use case in consumer electronics assembly. Automating the assembly of a tiny piece in consumer electronics is challenging, as multiple device variants require different production methods and the delicate metal structure requires precise pick-and-place and assembly control, as well as fine-tuned setup, often demanding additional debugging time and engineering resources. Using RobotStudio HyperReality, Foxconn\u2019s assembly robots are trained virtually, using synthetic data to perfect multiple real-world production processes in various scenarios, before moving them to the production line with 99 percent accuracy. By optimizing production lines virtually, Foxconn will reduce set-up times and costs by eliminating physical training and tests, and accelerate time-to-market for consumer electronics.<\/p>\n \u201cPrecision is everything in consumer electronics manufacturing and until now, this level of accuracy and fidelity just wasn\u2019t possible in simulation and digital twins,\u201d said Dr. Zhe Shi, Chief Digital Officer of Foxconn. \u201cWe\u2019re incredibly excited by the potential of ABB Robotics and Nvidia\u2019s collaboration, which enables parallel engineering for better designs, faster production ramp\u2011up and greater product evolution through advanced AI inference and understanding.\u201d<\/p>\n WORKR, a California based robotic workforce company that delivers robotic manufacturing solutions to industry, is extending the reach of this technology to small and medium manufacturers across the United States. At NVIDIA GTC 2026 (March 16-19, San Jose, CA), WORKR will demonstrate AI- powered robotic systems built on ABB technology, trained with synthetic data using Nvidia Omniverse libraries, and deployed without operators needing to know any programming. By combining ABB\u2019s industrial grade robotics with its proprietary WorkrCore\u2122 AI platform, the company is helping manufacturers address critical labor shortages with its robotic workforce that can learn new tasks in minutes and be operated by anyone.<\/p>\n \u201cThis collaboration is about making industrial AI deployable today,\u201d said Ken Macken, CEO & Founder of WORKR. \u201cTogether with ABB and Nvidia, we\u2019re proving that advanced automation can work for manufacturers of any size.\u201d<\/p>\n 1. ABB Robotics analysis<\/p>\n ABB Robotics\u00a0as one of the world\u2019s leading robotics companies, is the only company with a comprehensive and integrated AI-powered portfolio covering robots, cobots and Autonomous Mobile Robots (AMRs), designed and orchestrated by our value-creating software. We help companies of all sizes and sectors \u2013 from automotive to electronics and logistics \u2013 to outperform by becoming more resilient, flexible and efficient. ABB Robotics is at the forefront of developing and commercializing a new generation of Autonomous Versatile Robotics (AVR), leading a global innovation ecosystem of partners in advancing efficient hardware and intelligent software with industrial performance. The business employs approximately 7,000 people.\u00a0go.abb\/robotics<\/a><\/p>\n Image credit: ABB Robotics<\/p>\n","protected":false},"excerpt":{"rendered":"Insider Brief ABB Robotics is integrating Nvidia Omniverse libraries into its RobotStudio software to enable manufacturers to simulate…\n","protected":false},"author":2,"featured_media":28292,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_share_on_mastodon":"0"},"categories":[130],"tags":[232,4050,6007,4049,7132],"class_list":["post-28291","post","type-post","status-publish","format-standard","has-post-thumbnail","category-abb","tag-abb","tag-abb-robotics","tag-nvidia","tag-physical-ai","tag-robotics"],"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ch\/116199732203579223","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/posts\/28291","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/comments?post=28291"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/posts\/28291\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/media\/28292"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/media?parent=28291"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/categories?post=28291"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/tags?post=28291"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}